ANONYM.COMMUNITY
anonym.plus SD1 LINKABILITY
Case Study 11 of 20

Privacy Preservation in IoT: Anonymization Methods and Best Practices

Marios Vardalachakis, Manolis G. Tampouratzis · 2024-11

Research Source

Privacy Preservation in IoT: Anonymization Methods and Best Practices
Marios Vardalachakis, Manolis G. Tampouratzis · semantic_scholar · 2024-11

The Internet of Things (IoT) offers the most intense technological attempt, allowing objects to collect and exchange vast amounts of information efficiently. While this interconnectivity has various advantages, it also brings severe risks to each individual or organization regarding privacy. As the…

Executive Summary

This research paper examines a critical privacy challenge related to LINKABILITY — the ability to connect two pieces of information to the same person.

anonym.plus addresses this through 200+ entity types with multi-layer detection accessible across Desktop App (Windows/macOS/Linux) and additional platforms.

Root Cause: SD1 — LINKABILITY

The ability to connect two pieces of information to the same person. This is the foundational operation that makes PII dangerous. Nearly every pain point is an expression of linkability being created, exploited, or failing to be broken.

Irreducible truth: You cannot have useful data that is completely unlinkable AND completely useful. The very features that make data informative make it linkable. This is not a bug — it is information theory. The information content of a dataset and its linkability are the same property measured differently.

The Solution: How anonym.plus Addresses This

Detection Capabilities

anonym.plus identifies 200+ entity types including names, emails, SSNs, IBANs, passports, medical records, and country-specific identifiers. The local Presidio 2.2.357 + spaCy 3.8.11 architecture runs entirely offline — no cloud uploads, no internet required for detection. Supports 38 OCR languages via Tesseract for image anonymization.

Anonymization Methods

Redact is recommended for this pain point: completely removing fingerprint-contributing values eliminates the data points that algorithms combine into unique identifiers. Replace provides an alternative — substituting with non-unique alternatives prevents cross-device correlation while preserving document readability. For scenarios requiring reversibility, Encrypt (AES-256-GCM) enables authorized recovery of original values.

Architecture & Deployment

The REST API (Basic plan+) provides programmatic PII detection with Bearer token auth — the most accessible API entry point in the ecosystem.

Compliance Mapping

This pain point intersects with GDPR Article 5(1)(c) data minimization, ePrivacy Directive tracking consent.

anonym.plus's GDPR, HIPAA compliance coverage, combined with Fully offline — no server hosting, provides documented technical measures organizations can reference in their compliance documentation and regulatory submissions.

Product Specifications

SpecificationValue
Platform Version1.0.0 (desktop)
Entity Types200+
Accuracy95%+ (offline NLP)
Languages38 (OCR), 20+ (NLP)
Anonymization MethodsReplace, Redact, Mask, Hash (SHA-256), Encrypt (AES-256-GCM reversible)
PlatformsDesktop App (Windows/macOS/Linux)
PricingFree, Basic €149, Pro €399, Expert €499 (one-time lifetime)
HostingFully offline — no server
ComplianceGDPR, HIPAA